We extend the impact decomposition proposed by LeSage and Thomas-Agnan (2015) in the spatial interaction model to a more general framework, where the sets of origins and destinations can be different, and where the relevant attributes characterizing the origins do not coincide with those of the destinations. These extensions result in three flow data configurations which we study extensively: the square, the rectangular, and the non-cartesian cases. We propose numerical simplifications to compute the impacts, avoiding the inversion of a large filter matrix. These simplifications considerably reduce computation time; they can also be useful for prediction. Furthermore, we define local measures for the intra, origin, destination and network effects. Interestingly, these local measures can be aggregated at different levels of analysis. Finally, we illustrate our methodology in a case study using remittance flows all over the world.
Impact decomposition; local effects; spatial interaction autoregressive models; non-cartesian flow data;
- C13: Estimation: General
- C31: Cross-Sectional Models • Spatial Models • Treatment Effect Models • Quantile Regressions • Social Interaction Models
- C46: Specific Distributions • Specific Statistics
- C51: Model Construction and Estimation
- C65: Miscellaneous Mathematical Tools
Thibault Laurent, Paula Margaretic, and Christine Thomas-Agnan, “Generalizing impact computations for the autoregressive spatial interaction model”, TSE Working Paper, n. 22-1357, September 2022, revised February 2023.
TSE Working Paper, n. 22-1357, September 2022, revised February 2023